# `read.simulation.results.bigpurple` Read results of an EMOD simulation from its original location off the BigPurple filesystem ## Description Read results of an EMOD simulation from its original location off the BigPurple filesystem ## Usage ```r read.simulation.results.bigpurple( experiment_path, scenario_name, summarize_columns = c("Newly.Infected", "Newly.Tested.Positive", "Newly.Tested.Negative", "Population", "Infected", "On_ART", "Died", "Died_from_HIV", "Tested.Past.Year.or.On_ART", "Tested.Ever", "Diagnosed"), stratify_columns = c("Year", "Gender"), min_age_inclusive = 15, max_age_inclusive = 49, verbose = FALSE ) ``` ## Arguments Argument |Description ------------- |---------------- `experiment_path` | string pointing to the folder which contains the Simulation_XXXXXXXX folders. For example, /gpfs/scratch/kaftad01/experiments/Baseline-campaign_Nyanza_baseline_03112021_NoPrEP-Baseline___2022_02_17_21_34_51_660565 `scenario_name` | string for the name of the scenario being read. For example, you might use "baseline" for the baseline scenario. `summarize_columns` | a vector of strings containing names of columns to be aggregated via summation. Note that spaces in column names are replaced by a period ("."). For example, "Newly Infected" becomes "Newly.Infected". `stratify_columns` | a vector of strings containing names of columns by which we will stratify the data. For example, we might want to have a separate row in the dataset for each year, so we would set stratify_columns = c("Year") `min_age_inclusive` | an integer representing the minimum age to keep while reading the data (all ages below will be filtered out) `max_age_inclusive` | an integer representing the maximum age to keep while reading the data (all ages above will be filtered out) ## Details When a simulation is run on BigPurple, dtk-tools creates a simulation folder somewhere on BigPurple (the folder which contains the simulation folder is specified in simtools.ini using the parameter "sim_root"). In this folder is a set of folders - each one representing a different run of the simulation. These folders will look something like "Simulation_6CGUFHY7". The results of each simulation are stored within these folders. The results of an EMOD simulation are stored in a series of csv files titled "ReportHIVByAgeAndGender.csv". One of these files exists for each simulation run (typically 250 files). This function reads and aggregates those files into a single tibble. ## Value A tibble with columns incidence and Year